DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to communication filed on 03/23/2026.
Claims 1-5, 7-14, 17-23 are pending. Claims 6, and 15-16, have been canceled. Claims 21-23 are new. Claims 1, 11, 17 and 20 have been amended. Entry of this amendment is accepted and made of record.
Response to Arguments
Applicant's arguments filed 03/23/2026 have been fully considered but they are not persuasive.
With respect to claims 1-20 rejected under 35 USC 101, applicant argues that
the claims are not directed to a judicial exception (i.e. an abstract idea) and that even assuming arguendo that the Examiner were to find that the claims are directed to an abstract idea, the applicant submits that the claimed invention (and any alleged abstract idea to which the claimed invention may be alleged to be directed) is integrated into a practical application. Applicant further submits that even assuming arguendo that the Examiner were to find that the claimed invention and/or the alleged abstract idea to which the claimed invention is directed to is not integrated into a practical application, Applicant submits that the claimed invention includes elements that, when considered either alone or in combination, constitute significantly more than any alleged abstract idea to which the claimed invention may be directed (see second paragraph of page 10 of the remarks).
In response the examiner disagrees and submits that the amended claims are directed to an abstract idea without significantly more. The examiner submits that claim(s) 1, 11 and 20 recite(s) concepts related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion for “calculating, by the control system and using the telemetry data, a change in impedance in an electric line segment between two devices from the set of devices”; “analyzing, by the control system, the change in impedance in the electric line segment with a classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance”; “generating and generating by the control system, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment”; and “prioritizing remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices”.
The concepts discussed above can be considered to describe mental processes, namely concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. Although, the claim does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
Applicant further argues that the claims cannot be considered as directed to abstract as directed to a mental process since at least the step of “analyzing, by a multi-class classification machine learning model implemented by the control system, the change in impedance in the electric line segment, the multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance”, “generating, by the multi-class classification machine learning model implemented by the control system, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment”, and “directing, via input-output circuitry, maintenance operations on the electrical grid to remediate the cause of the change in the impedance in the electric line segment between the two devices at the location before remediation of the other cause of the other change in impedance in the other electric line segment between the other two devices from the set of devices based on the prioritization” cannot be considered mental processes because the steps are not practically performed in the human mind, because the human mind is not equipped to perform a claim to a specific time-estimation method for computers involving computer communication and a several-step manipulation data and because they could not, as practical matter, be performed entirely in a human’s mind (see last paragraph of page 10 through fourth line of page 11 of the remarks).
In response, the examiner disagrees and submits that the claimed steps of analyzing, generating, prioritizing includes concepts that can be considered to be mental since they described concepts that can performed in the human mind e.g. observation, evaluation, judgment, opinion i.e. analyzing a change in impedance; generating a cause of the change in impedance, and prioritizing a remediation of the cause of change. While the claimed limitations are performed by a classification machine learning model, the recitation of the machine learning model amounts to the recitation of a general purpose computer used to implement the abstract idea. The additional claimed element of “direct, via input-output circuitry, maintenance operations on the electrical grid to remediate the cause of the change in the impedance in the electric line segment between the two devices at the location before remediation of the other cause of the other change in impedance in the other electric line segment between the other two devices from the set of devices based on the prioritization” is considered insignificant extra solution activity in which the results are input/outputting as part as insignificant post-solution activity and are not applied in as to integrate the abstract idea into a practical application. In addition, the claim do not recite additional claim elements that can be considered significantly more than the judicial exception since the additional claim elements is mere data gathering recited at a high level of generality, generally liking the abstract idea to a field of use.
Applicant further submits that assuming arguendo, the claims do recite a judicial exception (e.g., a mental process) that can be practically performed in the human mind, the claims integrate any alleged abstract idea into a practical application that improves the functioning of a computer or technical field such as electrical grid operations, and that this improvement is reflected in the claims, such as through the analyzing, generating, prioritizing, and directing operations in claim 1. Applicant further adds that the broadest reasonable interpretation of the claim must be limited to computer implementation because, as discussed above, the entire claim scope cannot be practically preformed mentally and therefore integrates the abstract idea into a practical application that improves the functioning of a computer (see last paragraph of page 11 of the remarks).
In response, the examiner disagrees and submits that the claimed language do not reflect the alleged improvement to the operation of the computer and that the alleged improvements mentioned is generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) and as such is not indicative of a practical application of abstract idea.
Although applicant that a computer is recited in order to implement the abstract idea, the use of the general purpose computer is used as a tool to implement the abstract idea and as such it is not indicative of integration of the abstract idea into a practical application since as such it merely amounts to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Therefore claims 1-20, stand rejected under 35 USC 101 as being directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1, as exemplary, is summarized below in abbreviated form
A method for predicting causes of changes in power loss along electric line segments, the method comprising:
receiving, by a control system in near-real-time via a network, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid;
storing, by the control system, the telemetry data in a memory;
calculating, by the control system and using the telemetry data, a change in impedance in an electric line segment between two devices from the set of devices;
analyzing, by a multi-class classification machine learning model implemented by the control system, the change in impedance in the electric line segment the with a multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance;
generating, by the multi-class classification machine learning model implemented by the control system, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and
prioritizing, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices.
directing, via input-output circuitry, maintenance operations on the electrical grid to remediate the cause of the change in the impedance in the electric line segment between the two devices at the location before remediation of the other cause of the other change in impedance in the other electric line segment between the other two devices from the set of devices based on the prioritization.
The current 35 USC 101 analysis is based on the current guidance (2019
Revised Patent Subject Matter Eligibility Guidance, “2019 PEG’). The patent subject
matter eligibility analysis is threefold. First, via step 1, determine that the claim belongs
to a valid statutory class. Second, via step 2A, identify that an abstract idea is claimed in
prong one and if so, identify whether additional elements are recited that integrate the
abstract idea into a practical application in prong two. Finally, in step 2B, determine
whether the claims contain something significantly more than the abstract idea.
With respect to step 1, applied to the present application, the claims belong to
one of the statutory classes of a process (method claims 1-10); a product (apparatus of claims 11-19).
Step 2A of the 2019 Guidance is divided into two prongs. Prong 1 requires the
examiner to determine if the claims recite an abstract idea, and further requires that the
abstract idea belong to one of three enumerated groupings: mathematical concepts,
mental processes, and certain methods of organizing human activity.
With respect to step 2A, prong one, the claims recite an abstract idea.
Claim 1, summarized above in steps c-f, recites an abstract idea being highlighted in bold shown above, which include a mixture of two groupings of abstract ideas.
In claim 1, the limitations set forth in steps c-f of summarized steps of claim 1, and highlighted in bold (i.e. calculating, by the control system and using the telemetry data, a change in impedance in an electric line segment between two devices from the set of devices; analyzing the change in impedance in the electric line segment the with a multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance; generating, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and prioritizing, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices), can be considered to describe concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. These steps recited by the claim therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea. The limitations not in bold are considered to be additional elements that are not part of the abstract idea and need to be addressed in prong 2.
In summary, the highlighted steps in summarized claim 1 above therefore recite an abstract idea at Prong 1 of the 101 analysis.
Prong 2, of Step 2A of the 2019 Guidance requires the examiner to determine if the claims recite additional element(s) or a combination of additional elements which integrate the abstract idea into a practical application. This requires additional element(s) in the claim to apply, rely on, or use the abstract idea in a manner that imposes a meaningful limit on the abstract idea, such that the claim is more than a drafting effort designed to monopolize the abstract idea.
In claim 1 above, the additional elements have been left in normal font. The limitations considered additional elements claimed are “receiving, by a control system in near-real-time via a network, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid; which is mere data gathering recited at a high level of generality generally linking the abstract idea to a field of use and storing, by the control system, the telemetry data in a memory; …output of the multi-class classification machine learning model trained”, and the “electric line segments” merely ties in the abstract idea to a field of use and the results of the algorithm are merely output/stored (i.e. directing, via input-output circuitry, maintenance operations on the electrical grid…) as part of insignificant post-solution activity and are not used in any particular matter as to integrate the abstract idea in a practical application and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea.
Claim 1 recites the additional element(s) of using generic AI/ML technology, i.e. a multi-class classification machine learning model implemented by the control system, to perform data evaluations or calculations, as identified under Prong 1 above. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the use of the ” a multi-class classification machine learning model implemented by the control system” merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h). Therefore, the use of ” a multi-class classification machine learning model implemented by the control system” to perform steps that are otherwise abstract does not integrate the abstract idea into a practical application. See the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence1; and Example 47, ineligible claim 22.
Various considerations are used to determine whether the additional elements
are sufficient to integrate the abstract idea into a practical application. The claim does
not recite a specific machine. The claim does not effect a real-world transformation or
reduction of any particular article to a different state or thing. The claim does not
contain additional elements which describe the functioning of a computer, or which
describe a particular technology or technical field, which is being improved by the use of
the abstract idea. (This is understood in the sense of the claimed invention from
Diamond v Diehr, in which the claim as a whole recited a complete rubber-curing
process including a rubber-molding press, a timer, a temperature sensor adjacent the
mold cavity, and the steps of closing and opening the press, in which the recited use of
a mathematical calculation served to improve that particular technology by providing a
better estimate of the time when curing was complete. Here, the claim does not recite
carrying out any comparable technological process.) Instead the additional elements in
the claim appear to merely be generic computing elements and insignificant extra-
solution activity - merely gathering the relevant data necessary which is the input for the
mental process/math in the abstract idea, and then outputting a result of the abstract
idea. Based on these considerations, the additional elements in the claim do not appear
to integrate the abstract idea into a practical application. Instead, the claim would tend
to monopolize the abstract idea itself, across a wide variety of different practical
applications in the general field-of-use.
Step 2b of the 2019 Guidance requires the examiner to determine whether the
additional elements cause the claim to amount to significantly more than the abstract
idea itself. The considerations in this case are essentially the same as the
considerations for Prong 2 of Step 2a, and the same analysis leads to the conclusion
that the claim does not amount to significantly more than the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are mere data gathering/output recited at a high level of generality (steps a, b and e) and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 1, is rejected under 35 USC 101 as directed to an abstract idea without significantly more.
Dependent claims 2-10 and 21-23, when each is analyzed as a whole, are similarly held to be patent ineligible under 35 U.S.C. 101. The claims only recite further limitations which are part of the abstract idea discussed previously, and do not recite any additional elements which are sufficient to integrate the abstract idea into a practical application or to make the claims amount to significantly more than the abstract idea. The limitations merely add further details as to the type of data being received/input and used with the mental process and/or math steps recited in the independent claims, and also further calculations and math, so they are properly viewed as part of the recited abstract idea at Prong 1.
Claims 2-10 and 21-23 further expands on the abstract idea by appending additional steps which can be considered to describe concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers for calculating, by the control system, a difference between the measures of the impedance in the electric line segment from the two devices, (claim 8); calculated changes in the impedance in the electric line segments between the two devices,…determined cause of the change in impedance… is determined cause category comprising mild vegetation, moderate vegetation or severe vegetation (claim 9);” training, …the multi-class classification machine learning model using a historical training data set comprising the plurality of previously calculated changes in impedance in the electric line segment labeled with the plurality of known causes of the previously calculated changes in impedance” (claim 10), and which includes data characterization (i.e. wherein the telemetry data from a particular device in the set of devices includes impedance, voltage, or current at a position along an electric line corresponding to the particular device, claim 4; determined cause category comprising mild vegetation, moderate vegetation or severe vegetation (claim 9), “adjusting the cause of change to account for at least one of start or stop of single-phase motor” and mere data characterization (claim 22).
Although, the claims 2-10 does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
In summary, the steps in claims 2-10 discussed above, therefore recite an abstract idea at Prong 1 of the 101 analysis.
Prong 2, of Step 2A
With respect to claim 2-3, 5-6, 8-9, 21 and 23 the claims recite additional elements related which is mere data gathering recited at a high level of generality generally linking the abstract idea to a field of use, (i.e. telemetry data received via fiber optic network, claim 2; telemetry data received via passive-optical networking, claim 3; receives the telemetry data from the set of devices periodically, claim 5; receives the telemetry data from the set of devices at sub-second intervals, claim 6; retrieving,…measures of the impedance in the electric segment from the two devices, claim 8; retrieving…the plurality of previously calculated changes in the impedance in the electric line segment between the two devices claim 9; receiving input from downstream demand, claim 23) and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea and the results of the algorithm are merely output/stored (i.e. generating an alert on a user interface, claim 21) as part of insignificant post-solution activity and are not used in any particular matter as to integrate the abstract idea in a practical application and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea.
.
Prong 2, of Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 1-10 and 21-23 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Claim 11, as exemplary, as presented below recites:
An apparatus for predicting causes of changes in power loss along electric line segments, the apparatus comprising a processor and a memory storing software instructions that, when executed by the processor, cause the apparatus to:
receive, in near-real-time via a computer network, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid;
store the telemetry data in a memory;
calculate, using the telemetry data, a change in impedance in an electric line segment between two devices from the set of devices;
analyze, by a multi-class classification machine learning model, the change in impedance in the electric line segment, the multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance;
generate, by the multi-class classification machine learning model, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and
prioritize, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices
direct, via input-output circuitry, maintenance operations on the electrical grid to remediate the cause of the change in the impedance in the electric line segment between the two devices at the location before remediation of the other cause of the other change in impedance in the other electric line segment between the other two devices from the set of devices based on the prioritization.
The current 35 USC 101 analysis is based on the current guidance (2019
Revised Patent Subject Matter Eligibility Guidance, “2019 PEG’). The patent subject
matter eligibility analysis is threefold. First, via step 1, determine that the claim belongs
to a valid statutory class. Second, via step 2A, identify that an abstract idea is claimed in
prong one and if so, identify whether additional elements are recited that integrate the
abstract idea into a practical application in prong two. Finally, in step 2B, determine
whether the claims contain something significantly more than the abstract idea.
Step 2A of the 2019 Guidance is divided into two prongs. Prong 1 requires the
examiner to determine if the claims recite an abstract idea, and further requires that the
abstract idea belong to one of three enumerated groupings: mathematical concepts,
mental processes, and certain methods of organizing human activity.
With respect to step 2A, prong one, the claims recite an abstract idea.
Claim 11, summarized above in steps c-f, recites an abstract idea being highlighted in bold shown above, which include a mixture of two groupings of abstract ideas.
In claim 11, the limitations set forth in steps c-f of summarized steps of claim 1, and highlighted in bold (i.e. calculate,… a change in impedance in an electric line segment between two devices from the set of devices; analyze,… the change in impedance in the electric line segment, the multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance; generate, … a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and prioritize, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices.), can be considered to describe concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. These steps recited by the claim therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea. The limitations not in bold are considered to be additional elements that are not part of the abstract idea and need to be addressed in prong 2.
In summary, the highlighted steps in summarized claim 11 above therefore recite an abstract idea at Prong 1 of the 101 analysis.
Prong 2, of Step 2A of the 2019 Guidance requires the examiner to determine if the claims recite additional element(s) or a combination of additional elements which integrate the abstract idea into a practical application. This requires additional element(s) in the claim to apply, rely on, or use the abstract idea in a manner that imposes a meaningful limit on the abstract idea, such that the claim is more than a drafting effort designed to monopolize the abstract idea.
In claim 11 above, the additional elements have been left in normal font. The limitations considered additional elements claimed are “receiving, …, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid; storing, …, the telemetry data in a memory; …output of the multi-class classification machine learning model trained”, which is mere data gathering/output in which the results of the algorithm are outputted as part of insignificant post-solution activity and are not used in any particular manner as to integrate the abstract idea into a practical application and the “electric line segments” merely ties in the abstract idea to a field of use and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea, and the results of the algorithm are merely output/stored (i.e. directing, via input-output circuitry, maintenance operations on the electrical grid…) as part of insignificant post-solution activity and are not used in any particular matter as to integrate the abstract idea in a practical application and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea.
Claim 11 recites the additional element(s) of using generic AI/ML technology, i.e. a multi-class classification machine learning model implemented by the control system, to perform data evaluations or calculations, as identified under Prong 1 above. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the use of the ” a multi-class classification machine learning model implemented by the control system” merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h). Therefore, the use of ” a multi-class classification machine learning model implemented by the control system” to perform steps that are otherwise abstract does not integrate the abstract idea into a practical application. See the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence3; and Example 47, ineligible claim 24.
Various considerations are used to determine whether the additional elements
are sufficient to integrate the abstract idea into a practical application. The claim does
not recite a specific machine. The claim does not effect a real-world transformation or
reduction of any particular article to a different state or thing. The claim does not
contain additional elements which describe the functioning of a computer, or which
describe a particular technology or technical field, which is being improved by the use of
the abstract idea. (This is understood in the sense of the claimed invention from
Diamond v Diehr, in which the claim as a whole recited a complete rubber-curing
process including a rubber-molding press, a timer, a temperature sensor adjacent the
mold cavity, and the steps of closing and opening the press, in which the recited use of
a mathematical calculation served to improve that particular technology by providing a
better estimate of the time when curing was complete. Here, the claim does not recite
carrying out any comparable technological process.) Instead the additional elements in
the claim appear to merely be generic computing elements and insignificant extra-
solution activity - merely gathering the relevant data necessary which is the input for the
mental process/math in the abstract idea, and then outputting a result of the abstract
idea. Based on these considerations, the additional elements in the claim do not appear
to integrate the abstract idea into a practical application. Instead, the claim would tend
to monopolize the abstract idea itself, across a wide variety of different practical
applications in the general field-of-use.
Step 2b of the 2019 Guidance requires the examiner to determine whether the
additional elements cause the claim to amount to significantly more than the abstract
idea itself. The considerations in this case are essentially the same as the
considerations for Prong 2 of Step 2a, and the same analysis leads to the conclusion
that the claim does not amount to significantly more than the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are mere data gathering/output recited at a high level of generality (steps a, b and e) and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 11, is rejected under 35 USC 101 as directed to an abstract idea without significantly more.
Dependent claims 12-19, when each is analyzed as a whole, are similarly held to be patent ineligible under 35 U.S.C. 101. The claims only recite further limitations which are part of the abstract idea discussed previously, and do not recite any additional elements which are sufficient to integrate the abstract idea into a practical application or to make the claims amount to significantly more than the abstract idea. The limitations merely add further details as to the type of data being received/input and used with the mental process and/or math steps recited in the independent claims, and also further calculations and math, so they are properly viewed as part of the recited abstract idea at Prong 1.
Claims 12-19 further expands on the abstract idea by appending additional steps which can be considered to describe concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers for calculating, by the control system, a difference between the measures of the impedance in the electric line segment from the two devices, (claim 18); calculated changes in the impedance in the electric line segments between the two devices,…determined cause of the change in impedance… is determined cause category comprising mild vegetation, moderate vegetation or severe vegetation (claim 19); and which includes data characterization (i.e. wherein the telemetry data from a particular device in the set of devices includes impedance, voltage, or current at a position along an electric line corresponding to the particular device, claim 14; determined cause category comprising mild vegetation, moderate vegetation or severe vegetation (claim 19)).
Although, the claims 12-19 does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
In summary, the steps in claims 12-19 discussed above, therefore recite an abstract idea at Prong 1 of the 101 analysis.
Prong 2, of Step 2A
With respect to claim 12-13, 15-16, 18-19, the claims recite additional elements related which is mere data gathering recited at a high level of generality generally linking the abstract idea to a field of use, (i.e. telemetry data received via fiber optic network, claim 12; telemetry data received via passive-optical networking, claim 13; receives the telemetry data from the set of devices periodically, claim 15; receives the telemetry data from the set of devices at sub-second intervals, claim 16; retrieving,…measures of the impedance in the electric segment from the two devices, claim 18; retrieving…the plurality of previously calculated changes in the impedance in the electric line segment between the two devices ) and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea.
Prong 2, of Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 11-19 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Claim 20, as shown below in recite:
20. A computer program product for predicting causes of changes in power loss along electric line segments, the computer program product comprising at least one non-transitory computer-readable storage medium storing software instructions that, when executed by an apparatus, cause the apparatus to:
a. receive, in near-real-time via a computer network, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid;
b. store the telemetry data in a memory;
c. calculate, using the telemetry data, a change in impedance in an electric line segment between two devices from the set of devices; and
d. analyze, by a multi-class classification machine learning model, the change in impedance in the electric line segment with a, the multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance;
e. generate, by the multi-class classification machine learning model, a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and
f. prioritize, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices.
g. direct, via input-output circuitry, maintenance operations on the electrical grid to remediate the cause of the change in the impedance in the electric line segment between the two devices at the location before remediation of the other cause of the other change in impedance in the other electric line segment between the other two devices from the set of devices based on the prioritization.
The current 35 USC 101 analysis is based on the current guidance (2019 Revised Patent Subject Matter Eligibility Guidance, “2019 PEG’). The patent subject matter eligibility analysis is threefold. First, via step 1, determine that the claim belongs to a valid statutory class. Second, via step 2A, identify that an abstract idea is claimed in prong one and if so, identify whether additional elements are recited that integrate the abstract idea into a practical application in prong two. Finally, in step 2B, determine whether the claims contain something significantly more than the abstract idea.
Step 2A of the 2019 Guidance is divided into two prongs. Prong 1 requires the
examiner to determine if the claims recite an abstract idea, and further requires that the
abstract idea belong to one of three enumerated groupings: mathematical concepts,
mental processes, and certain methods of organizing human activity.
With respect to step 2A, prong one, the claims recite an abstract idea.
Claim 20, summarized above in steps c-f, recites an abstract idea being highlighted in bold shown above, which include a mixture of two groupings of abstract ideas.
In claim 20, the limitations set forth in steps c-f of summarized steps of claim 20, and highlighted in bold (i.e. calculate,… a change in impedance in an electric line segment between two devices from the set of devices; analyze,… the change in impedance in the electric line segment, the multi-class classification machine learning model trained on a plurality of previously calculated changes in impedance in the electric line segment and a plurality of known causes of the previously calculated changes in impedance; generate, … a cause of the change in the impedance in the electric line segment between the two devices and a location of the cause of the change in impedance as output of the multi-class classification machine learning model trained on the plurality of previously calculated changes in impedance in the electric line segment; and prioritize, in near-real-time, remediation of the cause of the change in the impedance in the electric line segment between the two devices relative to remediation of another cause of another change in impedance in another electric line segment between another two devices from the set of devices.), can be considered to describe concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. These steps recited by the claim therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea. The limitations not in bold are considered to be additional elements that are not part of the abstract idea and need to be addressed in prong 2.
In summary, the highlighted steps in summarized claim 20 above therefore recite an abstract idea at Prong 1 of the 101 analysis.
Prong 2, of Step 2A of the 2019 Guidance requires the examiner to determine if the claims recite additional element(s) or a combination of additional elements which integrate the abstract idea into a practical application. This requires additional element(s) in the claim to apply, rely on, or use the abstract idea in a manner that imposes a meaningful limit on the abstract idea, such that the claim is more than a drafting effort designed to monopolize the abstract idea.
In claim 20 above, the additional elements have been left in normal font. The limitations considered additional elements claimed are “receiving, …, telemetry data from a set of devices in an electrical grid, wherein the telemetry data includes data packets transmitted in sub-second intervals from the set of device in the electrical grid; storing, …, the telemetry data in a memory; …output of the multi-class classification machine learning model trained”, which is mere data gathering/output in which the results of the algorithm are outputted as part of insignificant post-solution activity and are not used in any particular manner as to integrate the abstract idea into a practical application and the “electric line segments” merely ties in the abstract idea to a field of use and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea, and the results of the algorithm are merely output/stored (i.e. directing, via input-output circuitry, maintenance operations on the electrical grid…) as part of insignificant post-solution activity and are not used in any particular matter as to integrate the abstract idea in a practical application and do not add significantly more to the abstract idea and only pertains as to where the data comes from in performing the abstract idea.
Claim 20 recites the additional element(s) of using generic AI/ML technology, i.e. a multi-class classification machine learning model implemented by the control system, to perform data evaluations or calculations, as identified under Prong 1 above. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the use of the ” a multi-class classification machine learning model implemented by the control system” merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h). Therefore, the use of ” a multi-class classification machine learning model implemented by the control system” to perform steps that are otherwise abstract does not integrate the abstract idea into a practical application. See the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence5; and Example 47, ineligible claim 26.
Various considerations are used to determine whether the additional elements
are sufficient to integrate the abstract idea into a practical application. The claim does
not recite a specific machine. The claim does not effect a real-world transformation or
reduction of any particular article to a different state or thing. The claim does not
contain additional elements which describe the functioning of a computer, or which
describe a particular technology or technical field, which is being improved by the use of
the abstract idea. (This is understood in the sense of the claimed invention from
Diamond v Diehr, in which the claim as a whole recited a complete rubber-curing
process including a rubber-molding press, a timer, a temperature sensor adjacent the
mold cavity, and the steps of closing and opening the press, in which the recited use of
a mathematical calculation served to improve that particular technology by providing a
better estimate of the time when curing was complete. Here, the claim does not recite
carrying out any comparable technological process.) Instead the additional elements in
the claim appear to merely be generic computing elements and insignificant extra-
solution activity - merely gathering the relevant data necessary which is the input for the
mental process/math in the abstract idea, and then outputting a result of the abstract
idea. Based on these considerations, the additional elements in the claim do not appear
to integrate the abstract idea into a practical application. Instead, the claim would tend
to monopolize the abstract idea itself, across a wide variety of different practical
applications in the general field-of-use.
Step 2b of the 2019 Guidance requires the examiner to determine whether the
additional elements cause the claim to amount to significantly more than the abstract
idea itself. The considerations in this case are essentially the same as the
considerations for Prong 2 of Step 2a, and the same analysis leads to the conclusion
that the claim does not amount to significantly more than the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are mere data gathering/output recited at a high level of generality (steps a, b and e) and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claim 20, is rejected under 35 USC 101 as directed to an abstract idea without significantly more.
Therefore, claims 1-23 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YARITZA H PEREZ BERMUDEZ whose telephone number is (571)270-1520. The examiner can normally be reached Monday-Friday.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at (571) 272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YARITZA H. PEREZ BERMUDEZ/
Examiner
Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
1 https://www.federalregister.gov/documents/2024/07/17/2024-15377/2024-guidance-update-on-patent-subject-matter-eligibility-including-on-artificial-intelligence
2 https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf
3 https://www.federalregister.gov/documents/2024/07/17/2024-15377/2024-guidance-update-on-patent-subject-matter-eligibility-including-on-artificial-intelligence
4 https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf
5 https://www.federalregister.gov/documents/2024/07/17/2024-15377/2024-guidance-update-on-patent-subject-matter-eligibility-including-on-artificial-intelligence
6 https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf
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